Given: online shop of spare parts for iPhones and Macbooks, in which 1500 pages.

Purpose of the article: Tell customers about the internal kitchen. Share experience with colleagues. Find clients.

Event chronology

  1. We're studying the market
  2. Install analytics
  3. Like the first advertising campaign
  4. Analyze
  5. Scaling up

We're studying the market.

We're watching the ads, making conclusions:

  • Competitors are lazy to explore the semantic core deeply and do not use low-frequency keywords such as "macbook pro 13" -You can make money from their negligence.
    2016-01-16 22-12-26 Window.png
    Our ads are on the screen, as it was made after the launch of the advertising campaign.
  • We are being replaced by service centers because they are willing to pay more for the customer than we are. - It is necessary to reject the words "replacement", "repair", etc. so as not to overlap with them.
  • Cellers of iPhones "merge" the budget for requests that are not relevant to them. - Judging by the screenshot, it is also advisable for us to compete with them, as they underestimate the rates because of low payback - not surprisingly.
    2016-01-16 21-52-38 Window.png

We partially compare prices with competitors. It happens that the customer is not able to compete - we tell him so. In this case, our prices were higher than the average, but the level of service fills this gap.

In our practice, there were online stores that automatically checked the prices of their competitors and, depending on them, lowered/increased their prices. There is a smart service, the cost of 15 000 per month, but keep in mind that total automation is not yet available, you have to let everything through your head and independently develop solutions.

After reading the reviews on Yandex Market and, this is a storehouse of information, we realized that many of our target audience are afraid to order the wrong part or are afraid to replace it by themselves - we have made an emphasis on it in the ads "Help to find the right one" and "Instructions for replacement".

We also recommend that you check your competitors' websites with to understand where they are getting their traffic and their audience. It wouldn't be superfluous to study your audience data on Google Analytics: look at the conversion in terms of devices, age, gender, interests, time and geography to adjust the rates accordingly.

Install analytics

Standard package:

Google Analytics

Let's not repeat, here is a separate article on the base setting.


The metric is needed to watch the web browser, install the segments for retargeting and e-commerce. Keep in mind that e-commerce in Metric and Google Analytics needs to be the first thing to do, it is difficult, you will need the help of programmers, but it is one of the best investments in analytics.

Google Tag Manager

An example of a good tone, GTM helps to set the counter codes on the site, the targets, to take the data without interfering with the site code, also GTM is necessary to set retargeting in Vkontake and Facebook.

K50 Statistics

Unlike Google Analitics, it allows you to disable/enable ads and adjust bets in the interface at once, but over time the service loses its relevance, we try to upload all the data into Analytics and work in it.

Questions answered by the analyst:

Advertising pays off?

If Context advertising brings you an average of 500 rubles, along with all the costs of its subsequent withholding (CAC), and the profit that it will bring you for the rest of your life will be 400 rubles (LTV), then this channel can be considered unprofitable (LTV < CAC)

Advertising gives rise to loyal customers?

For example, a month we attract 100 new visitors to the site, 1 out of 100 within 6 months to buy goods from us in the amount of 100 thousand rubles. Total 100 visitors, 1 of them will bring us 100 thousand rubles, within 6 months. Consequently, our retention rate is 1% (1 buyer / 100 visitors). With these figures, 1,000 visitors a year will bring us 1 million rubles. But after the shutdown of advertising, in 6 months we will have no clients left. Therefore, we are making a turnover, but we are not growing, and the growth will be if visitors stay with you for a longer period (green curve). That is, if you have a poor retention rate, then any marketing activity will go down.


How do I count on the praktie?

Unfortunately, it is impossible to calculate everything by 100%, as some orders go through calls, sarafan, re-sales and complex multi-channel sequences, especially in the field of services. Therefore, for each case are relevant to their own indicators, which are closest to the profit: the leaders, revenue, the profit itself, visits to the page of contacts. Be guided by common sense.

There are many ways to count LTV and CAC, from notepad to BigData tools. Don't try to build complex reports right away, implement advanced e-commerce, USER-ID, implement analytics in small iterations and measure the economic benefits from each. Professionals clinging to complex tasks because clinging to simple tasks is not interesting.

We're launching the first ad campaign

There are two main approaches:

  1. Other offers. Generate ads from YML, the main tools for this: K50 generator or Rocket from Wikimart.
  2. On demand. Collect keywords and select links for them using KeyKollector (~30% of irrelevant links) or JustMagic (~10% of irrelevant links, but expensive)

In fact, a combined approach is used. We didn't have YML, so we had to do it all in semi-manual mode in Excel:

  1. 20 thousand keywords were generated by multiplication method
    2016-01-17 14-44-39 Mediaplan - Google Tables.png
  2. Collected frequencies in the service (I recommend!) for each keyword and removed the words from the frequency 0
  3. For the rest of the array, the keywords have reached the frequency 50 (standard in ecommerce)
  4. References were selected manually from the main categories to the private ones, better, nothing was invented.

It was decided to structure the advertising campaign by category, as each category of goods, for example, batteries, has its own marginality and demand. It will be convenient to watch the statistics, turn off/on.


Standard UTM-label:



Usually, it's set up at the start to gather an audience right away. At the moment, the most popular platforms are Google with dynamic ads, when you show the visitor the goods in the product card which he was in, Vkontakte, Facebook, Yandex Direct and Target.Mail, the latter also with dynamic displays. Good article on the subject from Peter Abroskin, but without the use of dynamic advertisements.

ga1.png vk2.png fb1.png


When you're just starting a campaign, the first thing you need to do is to watch the web viewer to see briefly what requests users are going through and how they are behaving, as there is not enough other statistically significant data yet.

2015-12-26 12-53-41 - новинки для MAC — вебвизор — Яндекс.Метрика.png

When we have several thousand clicks, we analyze CTR, failures, depth, conversions and profit. Keep in mind that Google Analytics shows profit on all reports by attribution "Last indirect click", which means that if a visitor went to your site from contextual advertising, and then after 4 days came to him from the social network and bought, then such conversion will not be assigned to contextual advertising.

In our case, the user is going through a long enough way to conversion and 40% of the income falls on the next days after the visit. Therefore, we need to see the report on associated conversions:


To see the figures by campaign or phrase, use K50 Statistics (Attribution by last indirect click)


In K50 Statistics, you can filter keyword segments, such as all keywords with more than 100 and less than 4 CTR displays, and then adjust or disable them. And the service K50 Rules allows you to set automatic rules, for example, to disable all ads that have less than 1 ROI - convenient, but you need experience to configure.

Interpreter digits

We have uploaded all the figures using Microsoft Pivot by API Analytics.

2015-12-26 14-58-38 Analize.png

If the campaign shows a negative profit, we disable all the keywords in it, except those that show a positive result. If the result is positive, we try to maximize profits.


In K50 Statistics, we should analyze the main keywords/campaigns for DDR indicators (advertising expenses/profit from advertising) and "Share of screenings in special placement". That is, we look at how much we earn from each keyword and see if we can increase coverage.

For example, if the DDR is 90%, then 90% of our profits are spent on advertising (DDR, which is a cost/profit ratio), so we need to reduce the cost to the customer by lowering the rate. Conversely, if the DDRs are less than 40% and for special placement shows less than 30%, we can confidently raise the rate by 20%. From the point of view of mathematics, we do it in front of our eyes, but on soapy advertising budgets it is acceptable.

If you have more than 200 conversions per month, then you need to connect a conversion optimizer that will make predictions on more advanced mathematical algorithms, but most do not have so many conversions or they focus on a small number of keywords.

We scale up

Now we have a real experience of which categories of goods/services sell well - we begin to scale them up:

  • Enlarge the semantic core in width and depth
  • Test DSA Google
  • Connect Yandex Market and PriceLab to optimize bets
  • Remarketing

How to organize the work?

We work with medium and large projects, so first of all we carry out the tasks that are least expensive and will bring the customer profit. We perform the tasks ourselves in small iterations to estimate the result at once. We use Payment is made by fixing +% of sales or achievement of KPI. Conditionally, we calculate how much our time costs and divide the amount into a fix and a bonus.

2016-01-17 15-47-15 - Asana.png

I will be glad to hear what questions you find interesting to open them in the articles.

All "honestly"

All published reviews and advertising campaign results are documented on the page Thanks


"We have been working with Jam for a year now, particularly with Pavel, and I can recommend this specialist, who has a really high level of expertise. Pavel helps not only with setting up contextual advertising, but also with all the processes that affect it, together, we have implemented non-standard solutions with a directory, YML and retargeting. I would also like to note that we are constantly improving our advertising campaign and rely on real figures, such as ROI and LTV, and now we are expanding to the entire Russian market. The results are positive, thank you!"

Igor Motorin, director of company,

Get touch!

Write to us about your project, we will contact you within a couple of hours.

Next Previous
Our work
Stretch ceilings in Moscow and the region
2018 год

Stretch ceilings in Moscow and the regionHighly competitive market

In Moscow, there are 1000 companies competing in stretch ceilings: from independent contractors to federal-level companies. However, there are only 10 spots in contextual advertising, and they buy 80% of all traffic. The rest collect crumbs. What distinguishes successful companies? There is no accident or "a secret of the young business." We will share our vision on the example of a real case.

Before and after cooperation

Lead cost
Lead Conversion

Online auto parts store
2018 year

Online auto parts store

What was interesting about the project:

  • Made a matrix of covering categories of goods and brands of car manufacturers.
  • We picked up the correct attribution model.


$ 2300

Advertising budget for a month





Customer opinion


«I came to agency with the problem of high cost per lead and incorrect analytics, which we could not use to compare effectiveness of advertising channels with their expenses. The agency's experts developed a custom model to match conversion to channels, implemented electronic commerce, found problems in Google Analytics measurements and fixed them. What was exciting is that we got a matrix of our current and potential market reach with breakdown by car brand and spare part category, from which we drew a conclusion that we need to expand. Now we are systematically expanding the market reach and reducing the cost per lead. Contextual advertising brings a revenue of 400-600 thousand rubles per month»

Sergey Shumaev, Director,
Confirmation document

On-location real life quest games for children
2018 year

On-location real life quest games for children

In this case, we would like to talk about our approach in a small project for on location real life quest games for children.

What is unusual here?
  • A new product and market, there is no established demand, so it is necessary to search and test demand segments.
  • Beautiful reporting in Power BI

Sales funnel

$ 1840






$ 22,6

Cost per Lead



Customer opinion


«Hello everyone! I wanted to thank the team. These are the guys who set up advertising for us without any unnecessary questions from the professional point of view! I spent a lot of time choosing a marketing consultant, conducted a survey of 20 companies and chose 1jam, and this has been the best decision as of late! The guys did a quality job setting up context advertising, increased our quest game visits by about 30%. Advertising pays off, profit grows, analytics is set up, reports are on time, feedback is continuous. I highly recommend them to everyone!»

Dmitry Kusov, Director of
Confirmation document
Online-shop of garden equipment
2018 year

Online-shop of garden equipment

What was interesting about the project

  • Investigated the seasonality of each category of goods and launched them sequentially.
  • Developed a KPI project taking into account the outflow of customers to offline stores.



Advertising budget for a month




Leads online


Offline revenue growth

Client's opinion


«We started working with the agency in April 2018, the project team suggested we launch the categories of goods in sequence over the season in step with demand growth during the summer. One of our problems is that we have several offline stores for which we could not measure return on advertising investments. To solve this problem, we implemented call tracking, set up goals on the site and manually tracked the revenue trends by categories to collect the overall data and calculate the acceptable cost per lead by category. In general, I consider the task accomplished, we continue to work, I can recommend the team.»

Vladimir Frolov, Head of Marketing,
Confirmation document
Online tool shop «Wiha»
2015 year

Online tool shop «Wiha»

Learn more about the possibilities of generating advertising campaigns from XML

Advertising budget






Transaction conversion



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After you leave a request: interview ~15 minutes → guest audit access ~15 minutes → audit within 2 days → proposal approval → first iteration start. In our experience, it is real to start doing something in 2-3 days.

Менеджер проектов Александр

Project manager

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